Trending Research
Unleashing the Temporal-Spatial Reasoning Capacity of GPT for Training-Free Audio and Language Referenced Video Object Segmentation
In this paper, we propose an Audio-Language-Referenced SAM 2 (AL-Ref-SAM 2) pipeline to explore the training-free paradigm for audio and language-referenced video object segmentation, namely AVS and RVOS tasks.
Unifying Sequences, Structures, and Descriptions for Any-to-Any Protein Generation with the Large Multimodal Model HelixProtX
The experimental results affirm the advanced capabilities of HelixProtX, not only in generating functional descriptions from amino acid sequences but also in executing critical tasks such as designing protein sequences and structures from textual descriptions.
Distance-aware Molecule Graph Attention Network for Drug-Target Binding Affinity Prediction
The hierarchical attentive aggregation can capture spatial dependencies among atoms, as well as fuse the position-enhanced information with the capability of discriminating multiple spatial relations among atoms.
Automated Design of Agentic Systems
Researchers are investing substantial effort in developing powerful general-purpose agents, wherein Foundation Models are used as modules within agentic systems (e. g. Chain-of-Thought, Self-Reflection, Toolformer).
Autonomous LLM-driven research from data to human-verifiable research papers
As AI promises to accelerate scientific discovery, it remains unclear whether fully AI-driven research is possible and whether it can adhere to key scientific values, such as transparency, traceability and verifiability.
Highly accurate protein structure prediction with AlphaFold
PaddlePaddle/PaddleHelix
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Nature 2021
Accurate computational approaches are needed to address this gap and to enable large-scale structural bioinformatics.
SAM2Point: Segment Any 3D as Videos in Zero-shot and Promptable Manners
We introduce SAM2Point, a preliminary exploration adapting Segment Anything Model 2 (SAM 2) for zero-shot and promptable 3D segmentation.
LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset
efeslab/Nanoflow
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Studying how people interact with large language models (LLMs) in real-world scenarios is increasingly important due to their widespread use in various applications.
FunAudioLLM: Voice Understanding and Generation Foundation Models for Natural Interaction Between Humans and LLMs
This report introduces FunAudioLLM, a model family designed to enhance natural voice interactions between humans and large language models (LLMs).
